def check_status(self):
status = io_util.load_text_proto(self.status_filename(),
loop_pb2.LoopStatus, 'Status file')
if (status.name != self.status.name or
status.last_finished_round != self.status.last_finished_round or
status.current_round != self.status.current_round or
status.running_controller != self.running_controller):
logging.fatal('Inconsistent status between stored status and disk')
def write_final_stats(self):
"""Log and write final aggregated statistics to file system."""
fname = self.aggregate_stat_filename + '-00000-of-00001.pbtxt'
aggregate_stat = io_util.load_text_proto(
fname, deephol_stat_pb2.ProofAggregateStat, 'aggregate statistics')
if aggregate_stat is None:
tf.logging.warning('Could not read aggregate statistics "%s"',
fname)
return
tf.logging.info('Stats:\n%s',
stats.aggregate_stat_to_string(aggregate_stat))
open_goals = file_lines_set(self.open_goals_filename +
'-00000-of-00001.txt')
proven_goals = file_lines_set(self.proven_goals_filename +
'-00000-of-00001.txt')
never_proven = open_goals - proven_goals
num_open_goals = len(never_proven)
num_proven_goals = len(proven_goals)
tf.logging.info('Open goals: %d', num_open_goals)
tf.logging.info('Proved goals: %d', num_proven_goals)
perc_proven = 100.0 * num_proven_goals / float(num_open_goals +
num_proven_goals)
tf.logging.info('Percentage proven: %.2f', perc_proven)
with gfile.Open(self.proven_stats_filename, 'w') as f:
f.write('%d %d %.2f\n' %
(num_open_goals, num_proven_goals, perc_proven))
with gfile.Open(self.pretty_stats_filename, 'w') as f:
f.write('%s\n' % stats.detailed_statistics(aggregate_stat))
# Write cactus plot
if aggregate_stat.proof_closed_after_millis:
cactus_data = list(aggregate_stat.proof_closed_after_millis)
cactus_data.sort()
with gfile.Open(self.cactus_data_filename, 'w') as f:
f.write('\n'.join(map(str, cactus_data)))
fig = plot.figure()
plot.xlabel('Number of proofs closed')
plot.ylabel('Wall clock time in s')
plot.plot([ms * .001 for ms in cactus_data]) # convert to seconds
buf = io.BytesIO()
fig.savefig(buf, format='pdf', bbox_inches='tight')
with gfile.Open(self.cactus_plot_filename, 'wb') as f:
f.write(buf.getvalue())
def get_task_list(prover_tasks_file: Optional[str],
prover_task_list_file: Optional[str],
theorem_db: Optional[proof_assistant_pb2.TheoremDatabase],
splits, library_tags) -> List[proof_assistant_pb2.ProverTask]:
"""Get a list of theorem from either sources.
Whichever parameter is specified first is used as a source for the
tasks.
Args:
prover_tasks_file: File name for a text file with multiple ProverTasks in
each line or a recordio file depending on the extension.
prover_task_list_file: File name for a text protobuf prover_tasks_file.
theorem_db: TheoremDatabase object.
splits: List of splits to be considered. The list will be filtered for the
splits that are not specified.
library_tags: List of strings for the library tags to be processed. If
empty, then all library tags are allowed.
Returns:
List of tasks extracted.
"""
if prover_tasks_file:
tf.logging.info('Loading tasks from tasks file "%s".', prover_tasks_file)
return [
task for task in io_util.read_protos(prover_tasks_file,
proof_assistant_pb2.ProverTask)
if is_thm_included(task.goals[0], splits, library_tags)
]
elif prover_task_list_file:
tf.logging.info('Loading tasks from task list file "%s".',
prover_tasks_file)
task_list = io_util.load_text_proto(prover_task_list_file,
proof_assistant_pb2.ProverTaskList,
'prover task list')
return [
task for task in task_list.tasks
if is_thm_included(task.goals[0], splits, library_tags)
]
else:
tf.logging.info('Generating task list for theorem database.')
return create_tasks_for_theorem_db(theorem_db, splits, library_tags)
def main(argv):
runner.program_started()
if len(argv) > 1:
raise app.UsageError('Too many command-line arguments.')
assert FLAGS.root is not None, 'Required flag --root is missing.'
config = io_util.load_text_proto(FLAGS.config, loop_pb2.LoopConfig)
if (not FLAGS.rounds and not FLAGS.initial_examples
and not config.inherited_proof_logs):
logging.fatal('Loop setup requires either initial examples '
'or inherited proof logs')
controller_fingerprint = loop_meta.create_fingerprint()
meta = loop_meta.LoopMeta(FLAGS.root, config, controller_fingerprint,
False)
assert meta.status, 'Could not read status'
loop = loop_pipeline.LoopPipeline(meta, config)
if not FLAGS.rounds:
logging.info('Setting up loop...')
loop.setup_examples(FLAGS.initial_examples)
else:
for _ in xrange(FLAGS.rounds):
loop.perform_round(FLAGS.initial_examples)
def read_status(self):
self.status = io_util.load_text_proto(self.status_filename(),
loop_pb2.LoopStatus, 'Status file')
def get_task_list(prover_tasks_file: Optional[str],
prover_task_list_file: Optional[str],
tasks_by_fingerprint: Optional[Text],
theorem_db: Optional[proof_assistant_pb2.TheoremDatabase],
splits, library_tags) -> List[proof_assistant_pb2.ProverTask]:
"""Get a list of theorem from either sources.
Whichever parameter is specified first is used as a source for the
tasks.
Args:
prover_tasks_file: File name for a text file with multiple ProverTasks in
each line or a recordio file depending on the extension.
prover_task_list_file: File name for a text protobuf prover_tasks_file.
tasks_by_fingerprint: Comma-separated list of fingerprints from the theorem
database to generate a prover task for.
theorem_db: TheoremDatabase object.
splits: List of splits to be considered. The list will be filtered for the
splits that are not specified.
library_tags: List of strings for the library tags to be processed. If
empty, then all library tags are allowed.
Returns:
List of tasks extracted.
"""
if prover_tasks_file:
tf.logging.info('Loading tasks from tasks file "%s".', prover_tasks_file)
return [
task for task in io_util.read_protos(prover_tasks_file,
proof_assistant_pb2.ProverTask)
if is_thm_included(task.goals[0], splits, library_tags)
]
elif prover_task_list_file:
tf.logging.info('Loading tasks from task list file "%s".',
prover_tasks_file)
task_list = io_util.load_text_proto(prover_task_list_file,
proof_assistant_pb2.ProverTaskList,
'prover task list')
return [
task for task in task_list.tasks
if is_thm_included(task.goals[0], splits, library_tags)
]
elif tasks_by_fingerprint:
if not theorem_db:
tf.logging.fatal('Require a theorem database to create prover tasks from '
'fingerprints.')
tf.logging.info('Generating task list for fingerprint(s) %s',
tasks_by_fingerprint)
fingerprints = set([int(fp) for fp in tasks_by_fingerprint.split(',')])
theorems = []
for thm in theorem_db.theorems:
fingerprint = theorem_fingerprint.Fingerprint(thm)
if fingerprint in fingerprints:
fingerprints.remove(fingerprint)
theorems.append(thm)
if fingerprints:
tf.logging.error('Some fingerprints could not be found in theorem db: %s',
str(fingerprints))
return [
make_prover_task_for_goal(thm, thm, theorem_db.name) for thm in theorems
]
else:
tf.logging.info('Generating task list for theorem database.')
return create_tasks_for_theorem_db(theorem_db, splits, library_tags)